Classical and Probabilistic Information Retrieval Techniques: An Audit

  • Qaiser Abbas Department of Computer Science & IT, The University of Lahore, Sargodha, Pakistan
Keywords: Information Retrieval, Vector Space Model, Boolean Model, Probabilistic Models, Indexing Searching, Inference Network Model.


Information retrieval is acquiring particular information from large resources and presenting it according to the user’s need. The incredible increase in information resources on the Internet formulates the information retrieval procedure, a monotonous and complicated task for users. Due to over access of information, better methodology is required to retrieve the most appropriate information from different sources. The most important information retrieval methods include the probabilistic, fuzzy set, vector space, and boolean models. Each of these models usually are used for evaluating the connection between the question and the retrievable documents. These methods are based on the keyword and use lists of keywords to evaluate the information material. In this paper, we present a survey of these models so that their working methodology and limitations are discussed. This is an important understanding because it makes possible to select an information retrieval technique based on the basic requirements. The survey results showed that the existing model for knowledge recovery is somewhere short of what was planned. We have also discussed different areas of IR application where these models could be used.

How to Cite
Qaiser Abbas. (2021). Classical and Probabilistic Information Retrieval Techniques: An Audit. Lahore Garrison University Research Journal of Computer Science and Information Technology, 5(3), 84-91.